RETRACTED

Discrete Dynamics in Nature and Society has retracted the article titled “Operational Risk Assessment for International Transport Corridor: A Case Study of China-Pakistan Economic Corridor” [1]. A high level of overlap was identified with a thesis by Jing Xia, who graduated from the Chongqing Academy of Agricultural Sciences, Chongqing Jiaotong University, and participated in the design and conception of the research, questionnaire design, and data collection. The authors did not have the permission to publish, and the article is therefore being retracted with the agreement of all the authors and their institution.

Discrete Dynamics in Nature and Society
Volume 2019 (2019), Article ID 5730746, 7 pages
https://doi.org/10.1155/2019/5730746

Research Article

Operational Risk Assessment for International Transport Corridor: A Case Study of China-Pakistan Economic Corridor

Yang Lei,¹ Chengfeng Huang,¹ and Yuan Wu²

¹College of Economics and Management, Chongqing Jiao tong University, Chongqing 400074, China
²Chongqing Academy of Agricultural Sciences, Chongqing 401329, China

Correspondence should be addressed to Yuan Wu; 551794072@qq.com

Received 14 November 2018; Revised 30 January 2019; Accepted 18 February 2019; Published 4 March 2019

Academic Editor: Alicia Cordero

Copyright © 2019 Yang Lei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

The international transport corridor is the basis and carrier of economic and trade exchanges between countries and regions. International transport corridors span different countries and regions, coupled with the long distance, complicated transportation environment and process, which determines the potential risks of the operation of the transport corridors. Therefore, accurately identifying and assessing the risk of international channels are an important prerequisite for ensuring its safe and stable operation. The expert scoring method is used to collect the basic data of risk identification, and the hesitant fuzzy decision theory is introduced. The dependent linguistic ordered weighted geometric (DLOWG) operator and the Failure Mode and Effect Analysis (FMEA) method are used in combination. Taking the China-Pakistan Economic Corridor (CPEC) as an example, evaluate the operational risks of the international transport corridor. The research results show that corruption, terrorism, and policy stability are the top three risk factors in the operation of the China-Pakistan transport corridor. The risk management and control should focus on these three types of risks and strengthen the security management along the route. Strengthen policy docking and communication, maintain political stability, and strengthen antiterrorism cooperation.

1. Introduction

International transportation corridors are important carriers for international exchanges and trades [1], and their development and decline depend on the relationships between countries and levels of international economics and trades development [2]. International transport corridors are connected to the port and stations (including air and sea ports) facilities, supported by the network of transport lines on both sides, and are responsible for public and specific transport missions between countries or internationally [3]. China-Pakistan Economic Corridor (CPEC) is a collection of infrastructure projects that are currently under construction throughout Pakistan. CPEC is an important skeleton of China’s Belt and Road Initiative [4], and it is intended to rapidly modernize Pakistan infrastructure and strengthen its economy by the construction of modern transportation networks, numerous energy projects, and special economic zones. Moreover, it will build a modern integrated transportation corridor connecting China, Pakistan, and the Indian Ocean. And it can not only connect the Yangtze River Economic Belt with a “straight line” but also effectively connect with Central Asia, South Asia, the Middle East, and Europe. Therefore, the CPEC is considered to be a corridor of great strategic values.

International transport corridors span different countries and regions, coupled with the long distance, complicated transportation environment and process, which determines the potential risks of the operation of the transport corridors. Therefore, accurately identifying and assessing the risk of international corridor are an important prerequisite for ensuring its safe and stable operation. Ahmed et al. [5] Assess the risks faced by the energy construction project of CPEC from the perspective of energy assurance: economic burden, security threat, project completion delays, and lack of project feasibility studies. Qi and Jianming [6] utilize relevant data from the GTD, SATP, and PIPS databases to conduct a risk assessment of the terrorist threat faced at points along the CPEC. Yun [7] analyses political, economic, and security risks about CPEC based on macroscopic situations. Wenwu and Jing [8] identify the geopolitical risks of the China-Pakistan Economic Corridor from geopolitical risks, geoeconomic risks, and geotraditional/nontraditional security risks and constructed a georisk assessment model for the China-Pakistan Economic Corridor.

Risk assessment for international corridors mainly focuses on political risk and transportation risk based on qualitative evaluation methods, and quantitative methods are rare. From the above literature reviews, we can find that there are various types of potential risks in the process of CPEC’s advancement. Past researches mainly use description and discussion methods, and a little study tries to use expert evaluation (combination of qualitative and quantitative) to assess risks. Obviously, simply discussing the type of risk is not enough, and the traditional Delphi method is difficult to effectively assess the risks that are full of uncertainty and difficult to accurately describe.

Failure Mode and Effect Analysis (FMEA) is an analytical method used to determine potential failure modes and their causes, which can be used for risk assessment and management [9]. In order to deal with inherent fuzziness and uncertainty of expert judgment in risk evaluation in traditional FMEA, involving dependent linguistic ordered weighted geometric (DLOWG) operator has become very necessary [10]. The factors of risk priority number (RPN) of failure mode were treated as linguistic variables. Then linguistic judgments of a team of FMEA experts were aggregated by a developed DLOWG operator, in which the influence of unfair linguistic judging the aggregate aggregated result can be relieved by assigning low weights to those ‘false’ or ‘biased’ ones.

In this paper, the DLOWG operator and the FMEA are used to identify the operational risk factors of the CPEC, in order to identify key risks by quantitative methods, and provide suggestions for international transport risk management in CPEC.

2. Definition of International Transport Corridor Operational Risk

The history of human civilizations shows that economics development and modernizations are mainly carried out along natural or artificial corridors. Some corridors can be traced back to trade routes thousands of years ago (such as the ancient silk road), and some corridors are formed along the rivers or coastlines. In modern times, artificially constructed canals, roads, and railways have provided the basis for such corridors. Population and economic activities are mainly laid along the corridor. The generalized transport corridor is the sum of the flow of passengers and goods, the line, the vehicle, and the management system, and the transport route is the basic element of portraying the transport corridor. China’s “One Belt, One Road” initiative proposes jointly building six economic corridors on the land: (1) the New Eurasian Continental Bridge Economic Corridor, (2) China-Russia Economic Corridor, (3) China-Central Asia-West Asia Economic Corridor, (4) China-Indochina Economic Corridor, (5) Bangladesh-China-India-Myanmar Economic Corridor, and (6) China-Pakistan Economic Corridor [11]. In these transnational economic corridors, international transport corridors are the backbone and foundation of the economic corridors, which carry the circulation of goods and passengers.

As the transportation pillar of China’s “the Belt and Road” Initiative, the international transport corridors provide convenience for cross-border trade and shoulder the important mission of international transport. However, international corridor operations must fully consider various risks and effectively carry out risk control and management in order to maximize the international corridor's role in cross-border transportation. The operation of the international corridor refers to a normal and smooth state of the transportation system combined with various modes of transportation between countries. Therefore, the operational risk of the international transport corridor is defined as follows: the corridor itself is damaged, or the internal and external environment is disturbed, resulting in the corridor not being able to pass normally, resulting in a comprehensive loss.

3. Methodology

3.1. Hesitant Fuzzy Risk Assessment

Risk assessment is the first step in implementing risk management. It refers to the use of various systems, continuous understanding of various risks, and the analysis of potential causes of risk accidents before the occurrence of risk accidents. This is also the important link of project risk management [12]. Failure to accurately identify potential risks to the project will result in the best time to deal with these risks.

The risk assessment methods mainly include Delphi method, brainstorming method, checklist method, process combing analysis method, and data analysis method [13]. In view of the fact that the research object is the macr-operational risk of the international transportation corridor and the construction and operation of the China-Pakistan Economic Corridor is a long-term plan and there is currently no detailed operational data, the expert scoring method and the brainstorming method are used to identify the risk factors. Experts from the field of international relations research, university professors, transportation enterprise managers, and foreign experts are selected to form a FMEA expert group. The fuzzy comprehensive evaluation method is used to conduct a questionnaire survey to score the identified risk factors. In view of the shortcomings of the expert scoring method, the hesitation fuzzy set is used as the theoretical support [14, 15], and hesitant filling items are added in the questionnaire survey. If the expert's evaluation of the risk factor is uncertain, the hesitant evaluation language can be filled out multiple times to indicate uncertainty, and finally the data is further processed and calculated.

3.2. Indicators and Data

Based on the international standard “ISO31000 Risk Management Standards” [16] for risk assessment analysis, the risk factors including political risk, natural risk, environmental risk, operation and maintenance risk, and safety risk are analyzed in the form of expert group discussion. According to the results of the expert survey method and the actual situation of the transportation of CPEC, 14 risk factors were sorted out. The risk factor evaluation results are shown in Table 1.

Table 1: Evaluation indicators of risk factors for the operation of CPEC.

Categories
S/N
Risk factor
Source of risk factors

(failure mode)
(fault affecting factors)

Political risk
1
Policy stability
Changes in national policies, unsustainable policies, and separatist forces

2
Diplomatic environment
National geopolitics, discriminatory interventions by major countries

3
Policy change
Transportation and trade policy changes

4
Corruption
Corridor related management, transportation, customs official’s corruption

Natural risk
5
Natural force risk
Earthquakes, mudslides, mudslides, floods, lightning strikes, etc.

6
Climate risk
Typhoon, tornado, severe cold, rainy season, high temperature, etc.

Environmental risk
7
Nationality and religion
Corridor operation affects the interests of ethnic minorities and religious forces

8
Environmental coordination
Conflicts between surrounding ecology, human environment and channel operation

Operation and maintenance risk
9
technology
Different gauges in channel operation and different technical standards in maintenance

10
management
Organization and management of operation and maintenance

11
Cost
Cost sharing and operation of operation and maintenance

Security Risk
12
Terrorist activity
The destruction of the channel by terrorist activities

13
National war
The impact of wars on countries along the route

14
Social Security
Contradictions and factors affecting social stability along the corridor

4. Risk Identification Model for Corridor Operation

Risk identification refers to summarizing possible risk factors and ranking risk factors according to certain aspects or characteristics of the risks. Using the dependent linguistic ordered weighted geometric (DLOWG) operator, combined with FMEA method, the risk priority number (RPN) is calculated to obtain the risk factor ranking results.

4.1. The Dependent Linguistic Ordered Weighted Geometric Operator

A language assessment set is the basis for making decisions with linguistic variables. Assume discrete language scale set S= . The number of terms in S is generally odd, and the potential of the language terminology is . In order to facilitate calculation and avoid loss of decision information, based on the original discrete language scale set S, a new definition of extended continuous language set is defined as , where p is a sufficiently large natural number. The language information operation has the following definitions.

Definition 1. Assume that ,  , such that
(1) ;
(2) ;
(3) ;
(4) .

Definition 2. Assume that , , define as the distance between and , and . and the tightness ( and ) are proportional. The closer and are, the smaller the deviation is. If =0, thus = .

Definition 3. Supposing that LOWG: , is exponential weighted vector (linguistic weight vector), , and , since , is the largest element in the linguistic variable group and then LOWG is the n-dimensional linguistic ordered weighted geometric averaging operator.

Definition 4. Assuming that is a set of linguistic evaluation variable, . Then define the mean of the linguistic variable .

Definition 5. Assuming that is a set of linguistic evaluation variable, ; is the mean of the variable. This group of variables is arranged in descending order of numerical values, and the lower row after the arrangement is labeled . Then define the similarity of the large linguistic variable and as .

Definition 6. Assume that is the Weight of LOWG operator, and ; thus , because , ; thus , so is DLOWG operator.

From the derivation process, the following conclusions can be drawn: (1) DLOWG operator calculation is independent of variable ordering; (2) DLOWG operator calculation does not need to sort linguistic variables; (3) DLOWG operator can accurately describe expert evaluation value and average the closeness of the value and use this as a criterion to weight the evaluation value, reducing the impact of individual bias on decision-making.

4.2. Improve FMEA Evaluation Method

The Failure Mode and Effect Analysis (FMEA) evaluation method, originally proposed by the United States in the 1950s, was used for fighter operating system design [17]. In recent years, FMEA has been widely used in system reliability analysis and safety assessment. FMEA has the advantages of accurately identifying risks, determining risk impacts, and predicting ahead of time. Therefore, we use this method to identify the risk factors of international corridor operation and rank the risk factors by RPN in FMEA method.

In the FMEA method, the risk model “O, S, and D” is the Occurrence, Severity, and Detection of the risk model, respectively, and the three products are risk priority numbers, that is, . However, the traditional FMEA method has the defects of subjective judgment, inaccurate evaluation, and simple data processing. In view of this deficiency, we propose using DLOWG operator to determine the weight of expert scores, to minimize the impact of extreme bias on the evaluation results, and to ensure the accuracy and scientific of the evaluation while considering the expert opinions. Specific steps are as follows.

Firstly, assume that the assessment expert group identifies the risk patterns and evaluates the O, S, and D of each risk model according to the risk scoring criteria and , respectively, indicate linguistic evaluation values of the experts for the risk models . Use Definition 3 ~ Definition 5 to calculate each group of risk model given by expert (, and meet and .

Secondly, use Definition 3 to assemble the expert commentary set, , and ,and is the weighted operator of expert for O, S, and D of risk model . The specific calculation method is as follows;

Thirdly, according to the weight of Occurrence (O), severity (S), and Detection (D) of given risk model, utilize the RPN calculation formula to the evaluation result of the failure mode, and is defined by

Fourthly, the order of failure modes is determined by sorting according to . The larger is, the higher the risk of the failure mode . Identify key failure modes based on this principle to complete the risk identification process.

4.3. Improved FMEA Risk Factor Identification Model

Combined with the international corridor operational risk indicator system and risk factor content identification as described above and the improved FMEA risk assessment method based on DLOWG operator, an improved FMEA risk factor identification model for international channel operation is established as shown in Figure 1.

Figure 1: Improved FMEA risk factor identification model.

5. Identification of Corridor Operation Risk Factors

5.1. Expert Evaluation Set

In the China-Pakistan Economic Corridor Transportation Operational Risk Assessment Questionnaire, a total of 14 specific risk factors were identified in five categories as the failure mode in the FMEA assessment method . In order to facilitate the filling and collection of questionnaires, Arabic numerals are used instead of language terms. The corresponding language terminology is shown in Table 2.

Table 2: Collections of linguistic terms for risk factors.

Risk Factors
Linguistic Evaluation Set

1
2
3
4
5
6
7
8
9
10

O
Rarely happen
Between 1 and 3
Relatively less
Between 3 and 5
Occasionally Happens
Between 5 and 7
Happens very often
Between 7 and 9
Very easy to happen
Extremely easy to happen

S
Extremely less serious
Between 1 and 3
Not serious
Between 3 and 5
General
Between 5 and 7
Serious
Between 7 and 9
Very serious
Extremely serious

D
Extremely predictable
Between 1 and 3
Easy to predict
Between 3 and 5
Need to guard against
Between 5 and 7
Hard to predict
Between 7 and 9
Hard to predict
Extremely difficult to predict

Due to space limitations, the results of the questionnaires of four authoritative experts were selected for analysis. In the investigation, the risk Occurrence (O) and the risk Detection (D) adopt the hesitant fuzzy language set recognition method [18]; that is, the expert can fill in multiple language evaluation values according to his own judgment. For the risk severity (S), this paper uses the risk severity of the most likely occurrence of the expert as the evaluation set. That is, the language evaluation set of 14 risk factors by 4 experts is shown in Table 3. Among them, WO and WD language set is obtained by averaging the original evaluation of experts, and WS language set is the most likely risk of serious occurrence by experts. Degree as an evaluation set.

Table 3: Expert Evaluation Language Set.

Risk factor
WO
WS
WD

policy stability (M1)
(8.5,6.5,8,4)
(7,5,7,5)
(6.5,1.5,6,7)

Diplomatic environment (M2)
(8.5,6.5,6,3)
(6,5,6,4)
(8.5,2.5,6,6)

Policy change (M3)
(7.5,6.5,7,5)
(6,5,6,4)
(6,2,7,5)

Corruption (M4)
(8.5,7,9,7)
(8,7,4,5)
(8,5.5,5,7)

Natural force risk (M5)
(7.5,3.5,4,5)
(7,2,4,5)
(8.5,4.5,6,6)

Climate risk (M6)
(5,3.5,4,5)
(4,2,4,6)
(2.5,5,8,5)

Nationality and religion (M7)
(8.5,3.5,5,6)
(8,2,5,6)
(6.5,4.5,7,7)

Environmental coordination (M8)
(5,2,8,5)
(5,2,4,4)
(5,5.5,3,5)

Technology (M9)
(3.5,2,8,4)
(4,2,5,5)
(8,3.5,2,4)

management (M10)
(6.5,2.5,7,4)
(6,2,4,4)
(6,1.5,2,4)

Cost (M11)
(8.5,3,8,5)
(8,2,6,4)
(8,4,2,5)

Terrorist activity (M12)
(9.5,6.5,9,6)
(8,6,8,5)
(8.5,2,7,4)

National war (M13)
(6.5,7.5,3,4)
(5,6,10,4)
(8.5,2,9,3)

Social Security (M14)
(7,4.5,4,5)
(5,6,7,3)
(6,5,6,4)

5.2. Weight Coefficient

Use Definition 3 ~ Definition 5 to calculate each expert    of risk model , and the weight is satisfied that , and . The weight coefficient calculation results are shown in Table 4.

Table 4: Expert linguistic set weight coefficient.

Risk factor
WO
WS
WD

Policy stability (M1)
(0.25,0.22,0.24,0.28)
(0.26,0.23,0.22,0.29)
(0.31,0.2,0.3,0.2)

Diplomatic environment (M2)
(0.25,0.22,0.31,0.22)
(0.3,0.16,0.29,0.25)
(0.2,0.25,0.29,0.26)

Policy change (M3)
(0.3,0.12,0.27,0.32)
(0.3,0.16,0.29,0.25)
(0.26,0.21,0.21,0.32)

Corruption (M4)
(0.28,0.24,0.23,0.25)
(0.25,0.19,0.25,0.31)
(0.26,0.21,0.31,0.22)

Natural force risk (M5)
(0.31,0.24,0.13,0.32)
(0.28,0.2,0.21,0.3)
(0.2,0.25,0.29,0.26)

Climate risk (M6)
(0.21,0.27,0.2,0.33)
(0.23,0.25,0.25,0.27)
(0.16,0.28,0.23,0.33)

Nationality and religion (M7)
(0.25,0.26,0.24,0.26)
(0.23,0.23,0.29,0.25)
(0.31,0.26,0.22,0.2)

Environmental coordination (M8)
(0.22,0.2,0.25,0.33)
(0.26,0.22,0.23,0.3)
(0.24,0.23,0.21,0.33)

Technology (M9)
(0.19,0.23,0.27,0.3)
(0.19,0.21,0.29,0.31)
(0.27,0.33,0.13,0.27)

Management (M10)
(0.28,0.17,0.29,0.27)
(0.32,0.19,0.2,0.29)
(0.29,0.24,0.18,0.28)

Cost (M11)
(0.24,0.22,0.22,0.32)
(0.2,0.2,0.31,0.29)
(0.26,0.3,0.11,0.32)

Terrorist activity (M12)
(0.24,0.25,0.22,0.29)
(0.24,0.23,0.22,0.31)
(0.24,0.25,0.24,0.27)

National war (M13)
(0.3,0.21,0.19,0.3)
(0.28,0.25,0.16,0.31)
(0.27,0.28,0.2,0.25)

Social Security (M14)
(0.31,0.32,0.05,0.32)
(0.27,0.22,0.26,0.25)
(0.26,0.21,0.29,0.24)

5.3. Analysis of Evaluation Results

Aggregate expert reviews with formula , , , and are the weighted operators of the experts’ O, S, and D for the risk model. According to the expert interview and the actual situation of China-Pakistan transport corridor, determine the incidence rate (O), severity (S), and difficulty (D) weight of risk factors as . According to the RPN calculation formula (2), the evaluation result of the risk model is finally obtained, and the calculation result is shown in Table 5.

Table 5: Linguistic weighting operator.

Risk factor
O
S
D
RPN

Policy stability (M1)
6.378
5.871
4.843
5.68

Diplomatic environment (M2)
5.725
5.27
5.166
5.37

Policy change (M3)
6.365
5.27
4.629
5.36

Corruption (M4)
7.835
5.655
6.218
6.42

Natural force risk (M5)
5.048
4.343
5.986
5

Climate risk (M6)
4.349
3.755
4.984
4.27

Nationality and religion (M7)
5.446
4.74
6.089
5.33

Environmental coordination (M8)
4.695
3.643
4.595
4.21

Technology (M9)
4.01
3.935
4.205
4.04

Management (M10)
4.983
3.984
3.13
3.96

Cost (M11)
5.64
4.556
4.769
4.92

Terrorist activity (M12)
7.474
6.475
4.631
6.11

National war (M13)
5.019
5.45
4.43
5

Social Security (M14)
5.309
5.008
5.236
5.16

Risk prioritization can be obtained by combining the RPN corresponding to the risk factor in Table 5. The risk priority can be prioritized as .

It can be seen that the risk factor M4 has the largest language risk priority number (RPN) and should be the biggest concern of the relevant risk prevention system. Risk management and early warning should be given the highest priority; followed by risk factors M12, M1, M2, and M3 that should also be given great attention and focus on prevention; risk factors M7, M14, M5, and M13 risk priority level can be used as a general concern risk, with no need to focus on prevention; risk factors M11, M6, M8, and M9 risk priority level is low and may not be the focus on risk; risk factor M10 has the smallest risk priority number (RPN) in the evaluation and is negligible risk.

6. Conclusion

By defining the operational risk of the international corridor, this paper uses the brainstorming method and the expert scoring method to identify the operational risk factors of the CPEC, establishes international corridor operational risk factor identification model, and carries out the operational risk factors of the CPEC international corridor. The following conclusions are drawn: (1) the method—using the expert scoring method to evaluate the risk factors affecting the smooth operation of the corridor and using hesitant fuzzy collection for the scoring process—which can effectively collect expert hesitation opinions, reduce the loss of language information to a certain extent, and ensure the integrity and accuracy of expert scoring information; (2) using the DLOWG operator to calculate the expert score weight can effectively reduce the weight ratio of individual extreme scores and ensuring that the credibility and effectiveness of the assessment results are increased while considering the expert opinions; (3) based on the risk factors determined by the expert group, establishing an improved FMEA evaluation model based on DLOWG operator and applying it to evaluate International corridor operational risk of China-Pakistan Economic Corridor. The results show that corruption (M4), terrorist activities (M12), and politics stability (M1) are the top three risk factors for RPN. Risk management and control should focus on these three types of risks and strengthen public security management along the route. Strengthen policy docking and communication, maintain political stability, and strengthen counter-terrorism cooperation.

Data Availability

The data used to support the findings of this study are included within the article, and the experts’ questionnaire surveys data on risk assessment can be obtained by contacting the corresponding author.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Acknowledgments

This paper was supported by the National Social Science Foundation of China, no. 16AGJ007.

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